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import datasets |
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""" |
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domain in {'alarm', |
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'calling', |
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'event', |
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'messaging', |
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'music', |
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'news', |
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'people', |
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'recipes', |
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'reminder', |
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'timer', |
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'weather'} |
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""" |
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_URL = "https://fb.me/mtop_dataset" |
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_CITATION = """@article{li2020mtop, |
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title={MTOP: A comprehensive multilingual task-oriented semantic parsing benchmark}, |
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author={Li, Haoran and Arora, Abhinav and Chen, Shuohui and Gupta, Anchit and Gupta, Sonal and Mehdad, Yashar}, |
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journal={arXiv preprint arXiv:2008.09335}, |
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year={2020} |
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}""" |
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_DESCRIPTION = """ """ |
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class MtopConfig(datasets.BuilderConfig): |
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"""BuilderConfig for Mtop.""" |
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def __init__(self, **kwargs): |
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"""BuilderConfig for Mtop. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(MtopConfig, self).__init__(**kwargs) |
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class Mtop(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIGS = [ |
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MtopConfig( |
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name="mtop", |
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version=datasets.Version("1.0.0", ""), |
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description="Plain text", |
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), |
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] |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"idx": datasets.Value("string"), |
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"intent": datasets.Value("string"), |
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"spans": datasets.Value("string"), |
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"question": datasets.Value("string"), |
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"domain": datasets.Value("string"), |
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"lang": datasets.Value("string"), |
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"logical_form": datasets.Value("string"), |
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"tokenized_question": datasets.Value("string"), |
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} |
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), |
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supervised_keys=None, |
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homepage="", |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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filepath = dl_manager.download_and_extract(_URL) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": filepath,"split":"train"}), |
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": filepath,"split":"eval"}), |
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": filepath,"split":"test"}), |
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] |
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def _generate_examples(self, filepath, split): |
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"""This function returns the examples in the raw (text) form.""" |
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key = 0 |
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for lang in "de en es fr hi th".split(): |
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with open(f"{filepath}/mtop/{lang}/{split}.txt", encoding="utf-8") as f: |
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for example in f: |
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example = example.split("\t") |
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dict_example = dict(idx=example[0], |
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intent=example[1], |
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spans=example[2], |
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question=example[3], |
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domain=example[4], |
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lang=example[5], |
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logical_form=example[6], |
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tokenized_question=example[7]) |
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yield key, dict_example |
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key += 1 |
